NRC-Canada: building the state-of-the-art in sentiment analysis of tweets

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NRC-Canada: building the state-of-the-art in sentiment analysis of tweets
Authors: Saif M. Mohammad, Svetlana Kiritchenko, Xiaodan Zhu
Citation: missing booktitle  : 2013
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Database(s): Google Scholar cites
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Link(s): http://www.saifmohammad.com/WebDocs/sentimentMKZ.pdf
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NRC-Canada: building the state-of-the-art in sentiment analysis of tweets describes one of the best performing algorithms for Twitter sentiment analysis. The system successfully participated in the SemEval competition on sentiment analysis on Twitter posts and other short messages.

NRC-Canada would win again in 2014.[1]

[edit] Related papers

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  2. Measuring praise and criticism: inference of semantic orientation from association
  3. NRC-Canada-2014: detecting aspects and sentiment in customer reviews
  4. NRC-Canada-2014: recent improvements in sentiment analysis of tweets
  5. Sentiment analysis of short informal texts

[edit] See also

  1. NRC Emotion Lexicon

[edit] References

  1. https://docs.google.com/spreadsheets/d/1CmDicfEIxRgyoAix9BsVcC3qoRFEq0XDTSnBLVdavu8/edit#gid=0
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